How to Get Twitter Data using R {https://t.co/lJrAu2tCKh} #rstats #DataScience
— R-bloggers (@Rbloggers) March 5, 2022
Interaction Plot in R: How to Visualize Interaction Effect Between Variables {https://t.co/xukbymp89x} #rstats #DataScience
— R-bloggers (@Rbloggers) March 1, 2022
How to use pipes to clean up your R code {https://t.co/4XPpXS2SMl} #rstats #DataScience
— R-bloggers (@Rbloggers) March 2, 2022
Why RStudio Supports Python for Data Science {https://t.co/Tr51fN6ipJ} #rstats #DataScience
— R-bloggers (@Rbloggers) March 2, 2022
How to use Fonts and Icons in ggplot {https://t.co/Ysh8K8Te3y} #rstats #DataScience
— R-bloggers (@Rbloggers) March 4, 2022
3 Wild-Caught R and Python Applications {https://t.co/NdnkAZbVbI} #rstats #DataScience
— R-bloggers (@Rbloggers) March 6, 2022
4 Tips to Make Your Shiny Dashboard Faster {https://t.co/TEZdAPpPA4} #rstats #DataScience
— R-bloggers (@Rbloggers) March 6, 2022
Retweet Network Analysis in Cryptocurrencies {https://t.co/iM9dqYwjmw} #rstats #DataScience
— R-bloggers (@Rbloggers) March 6, 2022
Conditional RNN in keras (R) to deal with static features {https://t.co/KreJtA80Ae} #rstats #DataScience
— R-bloggers (@Rbloggers) March 6, 2022
Model Selection in Machine Learning {https://t.co/OvpkJisV1l} #rstats #DataScience
— R-bloggers (@Rbloggers) March 3, 2022
Convert data frame to array in R {https://t.co/35jA6UkuwW} #rstats #DataScience
— R-bloggers (@Rbloggers) March 7, 2022
Introducing torch for R {https://t.co/5jcDhAYwEr} #rstats #DataScience
— R-bloggers (@Rbloggers) March 3, 2022
How to use R Markdown (part one) {https://t.co/ILbCLOZLiS} #rstats #DataScience
— R-bloggers (@Rbloggers) February 13, 2022
How to Get Twitter Data using R {https://t.co/lJrAu2tCKh} #rstats #DataScience
— R-bloggers (@Rbloggers) March 5, 2022
Working With Databases and SQL in RStudio {https://t.co/uSYTMGhPBn} #rstats #DataScience
— R-bloggers (@Rbloggers) February 18, 2022
How To Make A PowerPoint Presentation Using R Markdown {https://t.co/KwWQ3Uq1uF} #rstats #DataScience
— R-bloggers (@Rbloggers) February 13, 2022
4 Ways to use colors in ggplot more efficiently {https://t.co/06nLp8KABo} #rstats #DataScience
— R-bloggers (@Rbloggers) February 19, 2022
Interaction Plot in R: How to Visualize Interaction Effect Between Variables {https://t.co/xukbymp89x} #rstats #DataScience
— R-bloggers (@Rbloggers) March 1, 2022
Beginner’s guide to machine learning in R (with step-by-step tutorial) {https://t.co/b3dTZTrrcG} #rstats #DataScience
— R-bloggers (@Rbloggers) February 10, 2022
Beginner’s guide to machine learning in R (with step-by-step tutorial) {https://t.co/btVK6vYGin} #rstats #DataScience
— R-bloggers (@Rbloggers) February 12, 2022
How to use pipes to clean up your R code {https://t.co/4XPpXS2SMl} #rstats #DataScience
— R-bloggers (@Rbloggers) March 2, 2022
11 New Books added to Big Book of R {https://t.co/zlBZjahGXb} #rstats #DataScience
— R-bloggers (@Rbloggers) February 6, 2022
Custom Google Analytics Dashboards with R: Downloading Data {https://t.co/V3gAmd5KKr} #rstats #DataScience
— R-bloggers (@Rbloggers) February 27, 2022
Export Data Frames into Multiple Excel Sheets in R {https://t.co/wCDnb2eZpj} #rstats #DataScience
— R-bloggers (@Rbloggers) February 13, 2022
---
title: "RBloggers Top Tweets"
output:
flexdashboard::flex_dashboard:
vertical_layout: scroll
source_code: embed
theme:
version: 4
bootswatch: yeti
css: styles/main.css
---
```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(httr)
library(lubridate)
library(jsonlite)
library(purrr)
rbloggers <- fromJSON("data/rbloggers.json")
get_tweet_embed <- function(user, status_id) {
url <-
stringr::str_glue(
"https://publish.twitter.com/oembed?url=https://twitter.com/{user}/status/{status_id}&partner=&hide_thread=false"
)
response <- GET(url) %>%
content()
return(shiny::HTML(response$html))
}
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### Top Tweets - 7 days {.tweet-wall}
```{r}
rblog_7 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 7, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_7_html <-
map2_chr(rblog_7$screen_name, rblog_7$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_7_html}"))
```
### Top Tweets - 30 days {.tweet-wall}
```{r}
rblog_30 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 30, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_30_html <-
map2_chr(rblog_30$screen_name, rblog_30$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_30_html}"))
```